2 citations · 2 across the 9 of their papers we have counts for
4 papers · 1 filter
From Mixing to Tearing: Graph Decomposition in Decentralized Optimization via Message Passing
Kuangyu Ding, Gesualdo Scutari
We study decentralized minimization of sums of smooth strongly convex functions, one per agent, with communication restricted to neighbors in a graph. Existing decentralized algori…
Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization
Kuangyu Ding, Kim-Chuan Toh
Sequence convergence to a boundary Karush--Kuhn--Tucker (KKT) point has long remained unclear for nonconvex mirror descent with Legendre kernels. The difficulty arises from the blo…
Non-KKT Accumulation in Entropic Mirror Descent
Kuangyu Ding, Kim-Chuan Toh
For mirror descent generated by a Legendre kernel, perhaps one of the most basic question in optimization is this: must every accumulation point of a bounded mirror descent sequenc…
A New Decomposition Paradigm for Graph-structured Nonlinear Programs via Message Passing
Kuangyu Ding, Marie Maros, Gesualdo Scutari
We study finite-sum nonlinear programs with localized variable coupling encoded by a (hyper)graph. We introduce a graph-compliant decomposition framework that brings message passin…